# Towards Automated Key-Point Detection in Images with Partial Pool View

arXiv: https://arxiv.org/abs/2208.05641 · HTML: https://mlsanity.com/paper/2208.05641/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 26 references that are in the map.
- First posted on arXiv 11 Aug 2022.

## Builds on (most cited first, 6 of 6)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age](https://mlsanity.com/paper/1606.05830/) (2016)
- [Real-Time Camera Pose Estimation for Sports Fields](https://mlsanity.com/paper/2003.14109/) (2020)
- [Automated Top View Registration of Broadcast Football Videos](https://mlsanity.com/paper/1703.01437/) (2017)
- [Localization of Ice-Rink for Broadcast Hockey Videos](https://mlsanity.com/paper/2104.10847/) (2021)
- [Swimmer Stroke Rate Estimation From Overhead Race Video](https://mlsanity.com/paper/2104.12056/) (2021)

## Abstract (arXiv)

Sports analytics has been an up-and-coming field of research among professional sporting organizations and academic institutions alike. With the insurgence and collection of athlete data, the primary goal of such analysis is to improve athletes' performance in a measurable and quantifiable manner. This work is aimed at alleviating some of the challenges encountered in the collection of adequate swimming data. Past works on this subject have shown that the detection and tracking of swimmers is feasible, but not without challenges. Among these challenges are pool localization and determining the relative positions of the swimmers relative to the pool. This work presents two contributions towards solving these challenges. First, we present a pool model with invariant key-points relevant for swimming analytics. Second, we study the detectability of such key-points in images with partial pool view, which are challenging but also quite common in swimming race videos.